Exploring Data-Driven Advocacy in Home Health Care Work

要旨

This paper explores opportunities and challenges for data-driven advocacy to support home care workers, an often overlooked group of low-wage, frontline health workers. First, we investigate what data to collect and how to collect it in ways that preserve privacy and avoid burdening workers. Second, we examine how workers and advocates could use collected data to strengthen individual and collective advocacy efforts. Our qualitative study with 11 workers and 15 advocates highlights tensions between workers’ desires for individual and immediate benefits and advocates’ preferences to prioritize more collective and long-term benefits. We also uncover discrepancies between participants’ expectations for how data might transform advocacy and their on-the-ground experiences collecting and using real data. Finally, we discuss future directions for data-driven worker advocacy, including combining different kinds of data to ameliorate challenges, leveraging advocates as data stewards, and accounting for workers’ and organizations’ heterogeneous goals.

受賞
Best Paper
著者
Joy Ming
Cornell, Ithaca, New York, United States
Hawi H. Tolera
Cornell University, Ithaca, New York, United States
Jiamin Tu
Cornell University, Ithaca, New York, United States
Ella Yitzhaki
Cornell University, Ithaca, New York, United States
Chit Sum Eunice Ngai
Cornell University, Ithaca, New York, United States
Madeline Sterling
Weill Cornell Medicine, New York, New York, United States
Ariel C. Avgar
Cornell University, Ithaca, New York, United States
Aditya Vashistha
Cornell University, Ithaca, New York, United States
Nicola Dell
Cornell Tech, New York, New York, United States
DOI

10.1145/3706598.3713086

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713086

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Better Work and Career

G414+G415
7 件の発表
2025-04-29 20:10:00
2025-04-29 21:40:00
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